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Evaluating AI Output

For ICs and managers reviewing AI-generated work — their own, their team's, or a vendor's. Seven chapters: the fluency illusion (Microsoft FAccT 2024, Anthropic sycophancy, Stanford HAI 2026); accuracy vs. usefulness as separate tests; three hallucination patterns (confident fabrication, plausible detail, stale fact) anchored in NIST AI 600-1 and the Vectara HHEM leaderboard; citation evaluation with the Mata v. Avianca anchor, 1,353+ court cases, Sixth Circuit $30K sanctions, and Deloitte Australia's AU$290K refund; demographic and regional bias with named cases (Bloomberg study, EEOC iTutorGroup, Workday Mobley class action); the verification habit grounded in Lally's 66-day study and BJ Fogg's B=MAP formula; and the close — your one-page verification playbook with three never-skip checks, one escalation rule, and the Friday review.

7

Chapters

~45 min

Duration

Intermediate

Level

No

Certification